Instructions to use mattbasedow/dollyforward-ltx23 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use mattbasedow/dollyforward-ltx23 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Lightricks/LTX-2.3-fp8", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("mattbasedow/dollyforward-ltx23") prompt = "-" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("Lightricks/LTX-2.3-fp8", dtype=torch.bfloat16, device_map="cuda")
pipe.load_lora_weights("mattbasedow/dollyforward-ltx23")
prompt = "-"
image = pipe(prompt).images[0]DOLLYFORWARD LTX-2.3
.jpg)
- Prompt
- -
Model description
LTX-2.3 LoRA trained to produce dolly forward camera movement. Use trigger word DOLLYFORWARD in your prompt.
Trigger words
You should use DOLLYFORWARD to trigger the image generation.
Download model
Download them in the Files & versions tab.
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